Exploiting Symmetric Temporally Sparse BPTT for Efficient RNN Training

Recurrent Neural Networks (RNNs) are useful in temporal sequence tasks. However, training RNNs involves dense matrix multiplications which require hardware that can support a large number of arithmetic operations and memory accesses. Implementing online training of RNNs on the edge calls for optimized algorithms for an efficient deployment on...

Revealing the Impact of Space-Charge Layers on the Li-Ion Transport in All-Solid-State Batteries

The influence of space-charge layers on the ionic charge transport over cathode-solid electrolyte interfaces in all-solid-state batteries remains unclear because of the difficulty to unravel it from other contributions to the ion transport over the interfaces. Here, we reveal the effect of the space-charge layers by systematically tuning the...